Characterizing Cluster-Based Frailty Phenotypes in a Multicenter Prospective Cohort of Kidney Transplant Candidates

Frailty is associated with a higher risk of death among kidney transplant candidates. Currently available frailty indices are often based on clinical impression, physical exam or an accumulation of deficits across domains of health. In this paper we investigate a clustering based approach that partitions the data based on similarities between individuals to generate phenotypes of kidney transplant candidates. We analyzed a multicenter cohort that included several features typically used to determine an individual's level of frailty. We present a clustering based phenotyping approach, where we investigated two clustering approaches-i.e. neural network based Self-Organizing Maps (SOM) with hierarchical clustering, and KAMILA (KAy-means for MIxed LArge data sets). Our clustering results partition the individuals across 3 distinct clusters. Clusters were used to generate and study feature-level phenotypes of each group.

Multiview Clustering to Identify Novel Kidney Donor Phenotypes for Assessing Graft Survival in Older Transplant Recipients

Key Points

An unsupervised machine learning clustering algorithm identified distinct deceased kidney donor phenotypes among older recipients. Recipients of certain donor phenotypes were at a relatively higher risk of all-cause graft loss even after accounting for recipient factors. The use of unsupervised clustering to support kidney allocation systems may be an important area for future study.

Background

Older transplant recipients are at a relatively increased risk of graft failure after transplantation, and some of this risk may relate to donor characteristics. Unsupervised clustering using machine learning may be a novel approach to identify donor phenotypes that may then be used to evaluate outcomes for older recipients. Using a cohort of older recipients, the purpose of this study was to (1 ) use unsupervised clustering to identify donor phenotypes and (2 ) determine the risk of death/graft failure for recipients of each donor phenotype.

Methods

We analyzed a nationally representative cohort of kidney transplant recipients aged 65 years or older captured using the Scientific Registry of Transplant Recipients between 2000 and 2017. Unsupervised clustering was used to generate phenotypes using donor characteristics inclusive of variables in the kidney donor risk index (KDRI). Cluster assignment was internally validated. Outcomes included all-cause graft failure (including mortality) and delayed graft function. Differences in the distribution of KDRI scores were also compared across the clusters. All-cause graft failure was compared for recipients of donor kidneys from each cluster using a multivariable Cox survival analysis.

Results

Overall, 23,558 donors were separated into five clusters. The area under the curve for internal validation of cluster assignment was 0.89. Recipients of donor kidneys from two clusters were found to be at high risk of all-cause graft failure relative to the lowest risk cluster (adjusted hazards ratio, 1.86; 95% confidence interval, 1.69 to 2.05 and 1.73; 95% confidence interval, 1.61 to 1.87). Only one of these high-risk clusters had high proportions of donors with established risk factors (i.e. , hypertension, diabetes). KDRI scores were similar for the highest and lowest risk clusters (1.40 [1.18–1.67] and 1.37 [1.15–1.65], respectively).

Conclusions

Unsupervised clustering can identify novel donor phenotypes comprising established donor characteristics that, in turn, may be associated with different risks of graft loss for older transplant recipients.

Prevalence of Frailty in Patients Referred to the Kidney Transplant Waitlist

Background

Comparisons between frailty assessment tools for waitlist candidates are a recognized priority area for kidney transplantation. We compared the prevalence of frailty using three established tools in a cohort of waitlist candidates.

Methods

Waitlist candidates were prospectively enrolled from 2016 to 2020 across five centers. Frailty was measured using the Frailty Phenotype (FP), a 37-variable frailty index (FI), and the Clinical Frailty Scale (CFS). The FI and CFS were dichotomized using established cutoffs. Agreement was compared using κ coefficients. Area under the receiver operating characteristic (ROC) curves were generated to compare the FI and CFS (treated as continuous measures) with the FP. Unadjusted associations between each frailty measure and time to death or waitlist withdrawal were determined using an unadjusted Cox proportional hazards model.

Results

Of 542 enrolled patients, 64% were male, 80% were White, and the mean age was 54±14 years. The prevalence of frailty by the FP was 16%. The mean FI score was 0.23±0.14, and the prevalence of frailty was 38% (score of ≥0.25). The median CFS score was three (IQR, 2-3), and the prevalence was 15% (score of ≥4). The κ values comparing the FP with the FI (0.44) and CFS (0.27) showed fair to moderate agreement. The area under the ROC curves for the FP and FI/CFS were 0.86 (good) and 0.69 (poor), respectively. Frailty by the CFS (HR, 2.10; 95% CI, 1.04 to 4.24) and FI (HR, 1.79; 95% CI, 1.00 to 3.21) was associated with death or permanent withdrawal. The association between frailty by the FP and death/withdrawal was not statistically significant (HR, 1.78; 95% CI, 0.79 to 3.71).

Conclusion

Frailty prevalence varies by the measurement tool used, and agreement between these measurements is fair to moderate. This has implications for determining the optimal frailty screening tool for use in those being evaluated for kidney transplant.

Frailty Screening in Chronic Kidney Disease: Current Perspectives

Frailty has been defined as a state of increased vulnerability as a consequence of deficit accumulation. Frailty screening has not yet been widely implemented into routine nephrology care. Patients with chronic kidney disease (CKD) are at high risk of being frail, and frailty has been associated with worse outcomes in this population. Standard management of CKD, including initiation of renal replacement therapies, may have decreased benefit or potentially cause harm in the presence of frailty, and a variety of interventions for modifying frailty in the CKD population have been proposed. The optimal means of screening for frailty in patients with kidney disease remains unclear. This review highlights the value of frailty screening in CKD by summarizing the outcomes associated with frailty and exploring proposed changes to the management of frail patients with CKD. Finally, we will propose a framework for how to implement frailty screening into standard nephrology care.

Intestinal commensal bacteria mediate lung mucosal immunity and promote resistance of newborn mice to infection

Immature mucosal defenses contribute to increased susceptibility of newborn infants to pathogens. Sparse knowledge of age-dependent changes in mucosal immunity has hampered improvements in neonatal morbidity because of infections. We report that exposure of neonatal mice to commensal bacteria immediately after birth is required for a robust host defense against bacterial pneumonia, the leading cause of death in newborn infants. This crucial window was characterized by an abrupt influx of interleukin-22 (IL-22)-producing group 3 innate lymphoid cells (IL-22+ILC3) into the lungs of newborn mice. This influx was dependent on sensing of commensal bacteria by intestinal mucosal dendritic cells. Disruption of postnatal commensal colonization or selective depletion of dendritic cells interrupted the migratory program of lung IL-22+ILC3 and made the newborn mice more susceptible to pneumonia, which was reversed by transfer of commensal bacteria after birth. Thus, the resistance of newborn mice to pneumonia relied on commensal bacteria-directed ILC3 influx into the lungs, which mediated IL-22-dependent host resistance to pneumonia during this developmental window. These data establish that postnatal colonization by intestinal commensal bacteria is pivotal in the development of the lung defenses of newborns.

Neutrophils inhibit tumor growth at early stages of tumor formation. (P2006)

Neutrophils are important innate immune cells involved in microbial clearance at sites of infection. However, the roles of neutrophils in cancer development are not clear. We hypothesized that neutrophils might mediate antitumor effects at the initial tumor formation stage. To test this hypothesis, we injected 2x106 mouse lung Lewis cancer cells into the flanks of C57BL/6 and Cxcr2-/- mice, the latter lack the receptor for ELR+ CXC neutrophil chemokines. We observed increased tumor growth in Cxcr2-/- mice as compared with controls within 3 weeks of injection. FACS analysis indicated fewer neutrophils and more IL-17-producing cells in the tumors of Cxcr2-/- mice than those of C57BL/6 mice. We further tested the roles of neutrophils using anti-Ly6G antibody depletion at the time of tumor cell injection. We demonstrated that tumors grew faster in the neutrophil depleted group, while the percentages of IL-17-producing cells in the tumors and the levels of G-CSF in the plasma were also increased in the absence of neutrophils. To test whether neutrophils have a direct cytotoxic effect on LLC cells, we performed in vitro cell killing assays. We demonstrated neutrophils isolated from both circulation and bone marrow exerted cytotoxic effects. In conclusion, by using Cxcr2-/- and neutrophil antibody-depleted C57BL/6 mice, we have demonstrated that initial tumor growth of LLC cells is enhanced in association with inaccessibility of neutrophils and activation of the IL-17/G-CSF axis.

The E3 ubiquitin ligase adaptor Ndfip1 regulates TH17 differentiation by limiting the production of pro-inflammatory cytokines (175.11)

Ndfip1 is an adaptor that promotes polyubiquitylation by the E3 ubiquitin ligase Itch. Mice that lack either Ndfip1 or Itch develop a severe TH2-mediated inflammatory disease at sites of environmental antigen exposure, including the lung. Here we demonstrate that lungs from Ndfip1-/- mice showed increased numbers of neutrophils and TH17 cells. This was not because Ndfip1-/- T cells are intrinsically biased towards TH17 differentiation. In fact, fewer Ndfip1-/- T cells differentiated into TH17 cells in vitro due to the overproduction of IL-4 production. Rather, TH17 differentiation in vivo was increased in Ndfip1-/- mice due to elevated numbers of IL-6 producing eosinophils. Interestingly, mice lacking both Ndfip1 and IL-4 had levels of IL-6 comparable to WT controls and these Ndfip1-/- IL-4-/- mice had fewer TH17 cells in their lungs compared to Ndfip1-/- IL-4+/+ mice. These results indicate that TH2 inflammation, such as that observed in Ndfip1-/- mice, can increase TH17 differentiation by recruiting IL-6 producing eosinophils into secondary lymphoid organs and tissues. This may explain why TH17 cells develop within an ongoing TH2 inflammatory response, such as asthma.